The third category includes intentions into messages and allow agents to negotiate during communication, reducing the non-stationarity caused by the uncertainty of agents' policies.
Some non-communication methods solve this problem by modelling others, i.e., predicting others' behaviours or goals [1]}, [2]}, [3]}.
By contrast, communication allows agents to share their intentions directly with others instead of inference. NeurComm [4]} takes policy fingerprints into communication
to reduce information loss and non-stationarity. Intention propagation [5]} allows agents to spread out initial decisions to their neighbours,
converging to the mean-field approximation of the joint policy. In IS [6]}, the agents model the environment dynamics to predict their imaginary paths and
share intentions with others by an attention module. Although intentions are helpful in coordination, agents may change their decisions after communication simultaneously in these
methods. In this way, the shared intentions cannot reflect agents' final actions, leading to potential message deceiving and miscoordination.
